A Two-Stage Multi-Objective Genetic-Fuzzy Mining Algorithm

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 會議論文 > Item 987654321/88828

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/88828

题名:	A Two-Stage Multi-Objective Genetic-Fuzzy Mining Algorithm
作者:	Chun-Hao Chen Ji-Syuan He Tzung-Pei Hong
贡献者:	資訊工程學系暨研究所
关键词:	Multi-objective genetic algorithm, clustering technique, membership function, taxonomy, fuzzy association rule.
日期:	2013-04-29
上传时间:	2013-04-26 11:08:43 (UTC+8)
摘要:	In this paper, we propose a two-stage multi-objective fuzzy mining algorithm for dealing with linguistic knowledge discovery. In the first stage, the multi-objective genetic lgorithm is used to derive a set of non-dominated membership functions (Pareto solutions) with two objective functions. In the second stage, the clustering technique is utilized to find representative solutions from the Pareto solutions. The epresentative solutions could be employed to mine fuzzy association rules according to the favorites of decision makers. Experiments on a simulation dataset are made and the results show the effectiveness of the proposed algorithm.
關聯:	SSCI
显示于类别:	[資訊工程學系暨研究所] 會議論文

文件中的档案:

没有与此文件相关的档案.

在機構典藏中所有的数据项都受到原著作权保护.

TAIR相关文章